Личните и географските имена в българския и сръбския превод на Стишния пролог (по материал от месец март)

The paper presents a comparative study of the personal and geographic names in the two complete Slavic translations of the Byzantine Versified Synaxarion, namely the Bulgarian and Serbian Prolog Stišnoj, which appeared around the first half of the 14 th century. On the basis of the March texts in seven South Slavic manuscripts, the differences in the rendering of the personal names are analysed on the level of phonetics, orthography, morphology and word formation. The data allow the following conclusions: 1) The differences in the forms of these names in the Bulgarian and Serbian Prolog Stišnoj give further arguments supporting their independent origin; 2) Several specific tendencies are noted which more or less differentiate them. The Bulgarian translation reproduces more accurately the graphics of the original names, allows dativus possessivus, often replaces the Greek anthroponyms and toponyms with adjectives, presents many local names in the plural, and sometimes retains Greek nominative endings in masculine personal names. The Serbian translation, on the other hand, follows more often the Byzantine pronunciation of the names, complies more strictly with their grammatical characteristics (case, number), separates more often the ending -ς from the stem, and incorporates the accusative ending -ν into the stem of certain anthroponyms several times. 3) The tendency towards Slavicisation of the personal names is nearly the same in both translations and cannot be viewed as peculiar of either of them.

Crowdsourcing language change with smartphone applications

Crowdsourcing linguistic phenomena with smartphone applications is relatively new. In linguistics, apps have predominantly been developed to create pronunciation dictionaries, to train acoustic models, and to archive endangered languages. This paper presents the first account of how apps can be used to collect data suitable for documenting language change: we created an app, Dialäkt Äpp (DÄ), which predicts users’ dialects. For 16 linguistic variables, users select a dialectal variant from a drop-down menu. DÄ then geographically locates the user’s dialect by suggesting a list of communes where dialect variants most similar to their choices are used. Underlying this prediction are 16 maps from the historical Linguistic Atlas of German-speaking Switzerland, which documents the linguistic situation around 1950. Where users disagree with the prediction, they can indicate what they consider to be their dialect’s location. With this information, the 16 variables can be assessed for language change. Thanks to the playfulness of its functionality, DÄ has reached many users; our linguistic analyses are based on data from nearly 60,000 speakers. Results reveal a relative stability for phonetic variables, while lexical and morphological variables seem more prone to change. Crowdsourcing large amounts of dialect data with smartphone apps has the potential to complement existing data collection techniques and to provide evidence that traditional methods cannot, with normal resources, hope to gather. Nonetheless, it is important to emphasize a range of methodological caveats, including sparse knowledge of users’ linguistic backgrounds (users only indicate age, sex) and users’ self-declaration of their dialect. These are discussed and evaluated in detail here. Findings remain intriguing nevertheless: as a means of quality control, we report that traditional dialectological methods have revealed trends similar to those found by the app. This underlines the validity of the crowdsourcing method. We are presently extending DÄ architecture to other languages.

English Dialect App

Do you pronounce the /r/ in 'arm'? Do you call a shelf a 'sheuf'? And what on earth is a 'hoddy-doddy'? There is extensive variation in English dialects: this is why your answers to such questions will allow this app to localize your broader dialect region on a map of England. Did your home dialect change over time? Our algorithm is based on historical data from the Survey of English Dialects. If it guesses where you are from correctly, your home dialect has probably remained stable over the past decades. If the guess is far off, however, it is probably because of dialect change. - Can we localize your dialect based on your pronunciation of 26 words? - Record your dialect and listen to recordings of other users and to historical dialect recordings! - Choose a pronunciation variant, e.g. 'sheuf', and discover where in England it is used...or choose a place and explore its dialect!

Propuesta de actividades de autoaprendizaje para el nivel A2 de lengua inglesa en la plataforma Moodle

Los objetivos de este proyecto son proporcionar la teoría, los ejercicios y otros recursos necesarios para que los alumnos de la EUIT de Telecomunicación con un nivel A1 en el Marco Común Europeo de Referencia para las Lenguas (MCERL) puedan obtener el nivel A2 en inglés sin necesidad de asistir a clases ni matricularse en cursos presenciales. La plataforma utilizada para conseguir este fin es Moodle, siendo utilizada en la página web de ILLLab. Este curso online sirve para alcanzar los conocimientos requeridos en la asignatura optativa Introduction to English for Professional and Academic Communication I que parte del nivel B1. Se realiza una propuesta de la gramática con sus correspondientes ejemplos y ejercicios basados todos ellos en adaptaciones de actividades publicadas en un corpus de libros de texto. Se añaden recursos (pequeñas lecturas, videos, enlaces) que se consideran apropiados para el tema tratado. Por otro lado, también se persigue solucionar el problema de los cursos de idiomas basados en e-learning ya que no proporcionan las herramientas necesarias para poner en práctica la expresión oral. Para ello, se aporta una aplicación basada en técnicas de reconocimiento de voz, con tres actividades en las que los resultados han de darse de forma hablada y con la correcta pronunciación. Así, se busca dar una base de conocimientos y experiencias prácticas para futuros proyectos basados en herramientas de síntesis y reconocimiento de voz, además de buscar un nuevo enfoque en el estudio de idiomas. Abstract: The objectives of this project are to provide the theory, exercises and other resources for students at the EUIT Telecommunications with A1 level in the Common European Framework of Reference for Languages (MCERL) in order to get A2 level in English without attending face-to-face courses. The platform used to achieve this aim is Moodle, which is currently being used in ILLLab website. This online course is due to attain the knowledge required in the optional subject Introduction to English for Professional and Academic Communication I which is based on the B1 level. It is a proposal of grammar with corresponding examples and exercises all based on adaptations of activities posted on a corpus of textbooks. It also adds resources (short readings, videos or links) that are appropriate for the subject. On the other hand, this project aims to solve the problem of language courses based on e-learning because these do not usually provide the student with the necessary tools to practice speaking. For this, we develop an application based on speech recognition techniques and propose three activities to practice speaking, and pronunciation. The proposal seeks to provide knowledge and practical experience for future projects based on synthesis tools and voice recognition, and means a new approach to e-learning courses for the study of languages.

Actividades online de vocabulario y pronunciación para el nivel de la lengua inglesa A2

El objetivo del presente proyecto es proporcionar una actividad de la pronunciación y repaso de vocabulario en lengua inglesa para la plataforma Moodle alojada en la página web de Integrated Language Learning Lab (ILLLab). La página web ILLLab tiene el objetivo de que los alumnos de la EUIT de Telecomunicación de la UPM con un nivel de inglés A2 según el Marco Común Europeo de Referencia para las Lenguas (MCERL), puedan trabajar de manera autónoma para avanzar hacia el nivel B2 en inglés. La UPM exige estos conocimientos de nivel de inglés para cursar la asignatura English for Professional and Academic Communication (EPAC) de carácter obligatorio e impartida en el séptimo semestre del Grado en Ingeniería de Telecomunicaciones. Asimismo, se persigue abordar el problema de las escasas actividades de expresión oral de las plataformas de autoaprendizaje se dedican a la formación en idiomas y, más concretamente, al inglés. Con ese fin, se proporciona una herramienta basada en sistemas de reconocimiento de voz para que el usuario practique la pronunciación de las palabras inglesas. En el primer capítulo del trabajo se introduce la aplicación Traffic Lights, explicando sus orígenes y en qué consiste. En el segundo capítulo se abordan aspectos teóricos relacionados con el reconocimiento de voz y se comenta sus funciones principales y las aplicaciones actuales para las que se usa. El tercer capítulo ofrece una explicación detallada de los diferentes lenguajes utilizados para la realización del proyecto, así como de su código desarrollado. En el cuarto capítulo se plantea un manual de usuario de la aplicación, exponiendo al usuario cómo funciona la aplicación y un ejemplo de uso. Además, se añade varias secciones para el administrador de la aplicación, en las que se especifica cómo agregar nuevas palabras en la base de datos y hacer cambios en el tiempo estimado que el usuario tiene para acabar una partida del juego. ABSTRACT: The objective of the present project is to provide an activity of pronunciation and vocabulary review in English language within the platform Moodle hosted at the Integrated Language Learning Lab (ILLLab) website. The ILLLab website has the aim to provide students at the EUIT of Telecommunication in the UPM with activities to develop their A2 level according to the Common European Framework of Reference for Languages (CEFR). In the platform, students can work independently to advance towards a B2 level in English. The UPM requires this level of English proficiency for enrolling in the compulsory subject English for Professional and Academic Communication (EPAC) taught in the seventh semester of the Degree in Telecommunications Engineering. Likewise, this project tries to provide alternatives to solve the problem of scarce speaking activities included in the learning platforms that offer language courses, and specifically, English language courses. For this purpose, it provides a tool based on speech recognition systems so that the user can practice the pronunciation of English words. The first chapter of the project introduces the application Traffic Lights, explaining its origins and what it is. The second chapter deals with theoretical aspects related with speech recognition and comments their main features and current applications for which it is generally used. The third chapter provides a detailed explanation of the different programming languages used for the implementation of the project and reviews its code development. The fourth chapter presents an application user manual, exposing to the user how the application works and an example of use. Also, several sections are added addressed to the application administrator, which specify how to add new words to the database and how to make changes in the original stings as could be the estimated time that the user has to finish the game.

Generating segmental foreign accent

For most of us, speaking in a non-native language involves deviating to some extent from native pronunciation norms. However, the detailed basis for foreign accent (FA) remains elusive, in part due to methodological challenges in isolating segmental from suprasegmental factors. The current study examines the role of segmental features in conveying FA through the use of a generative approach in which accent is localised to single consonantal segments. Three techniques are evaluated: the first requires a highly-proficiency bilingual to produce words with isolated accented segments; the second uses cross-splicing of context-dependent consonants from the non-native language into native words; the third employs hidden Markov model synthesis to blend voice models for both languages. Using English and Spanish as the native/non-native languages respectively, listener cohorts from both languages identified words and rated their degree of FA. All techniques were capable of generating accented words, but to differing degrees. Naturally-produced speech led to the strongest FA ratings and synthetic speech the weakest, which we interpret as the outcome of over-smoothing. Nevertheless, the flexibility offered by synthesising localised accent encourages further development of the method.

Linguistic aspects of speech synthesis.

The conversion of text to speech is seen as an analysis of the input text to obtain a common underlying linguistic description, followed by a synthesis of the output speech waveform from this fundamental specification. Hence, the comprehensive linguistic structure serving as the substrate for an utterance must be discovered by analysis from the text. The pronunciation of individual words in unrestricted text is determined by morphological analysis or letter-to-sound conversion, followed by specification of the word-level stress contour. In addition, many text character strings, such as titles, numbers, and acronyms, are abbreviations for normal words, which must be derived. To further refine these pronunciations and to discover the prosodic structure of the utterance, word part of speech must be computed, followed by a phrase-level parsing. From this structure the prosodic structure of the utterance can be determined, which is needed in order to specify the durational framework and fundamental frequency contour of the utterance. In discourse contexts, several factors such as the specification of new and old information, contrast, and pronominal reference can be used to further modify the prosodic specification. When the prosodic correlates have been computed and the segmental sequence is assembled, a complete input suitable for speech synthesis has been determined. Lastly, multilingual systems utilizing rule frameworks are mentioned, and future directions are characterized.

Metropolitan seminars in art /

Pronunciation guide, 2 pages in pocket of each portfolio.

The works of William Shakespeare : the plays edited from the folio of MDCXXIII, with various readings from all the editions and all the commentators, notes, introductory remarks, a historical sketch of the text, an account of the rise and progress of the English drama, a memoir of the poet, and an essay upon his genius /

Publisher's advertisement (12 p.) at beginning of v. 2.

Lippincott's new gazetteer A complete pronouncing gazetter ofr geographical dictionary of the world, containing the most recent and authentic information respecting the countries, cities, towns, resorts, islands, rivers, mountains, seas, lakes, etc., in every portion of the globe;

First published 1855. The present publication printed from new type from title-page to cover, is a new work, embodying little more than the framework of its predecessor, together with its system of pronunciation. cf. Publisher's note.

Les parlers parisiens ... : anthologie phonétique /

Cover title: Proben pariser aussprache ... specimens of Parisian pronunciation.

Romantic languages pamphlets

A collection of miscellaneous pamphlets on the romance languages.

Encyklopädisches englisch-deutsches und deutsch-englisches wörterbuch; ein parallelwerk zu Sachs-Villatte's französisch-deutschem und deutsch-französischem wörterbuche; mit angabe der aussprache nach dem phonetischen system der methode Toussaint-Langenscheidt ...

To v. 4 is prefixed: German, Austrian and Swiss measures, weights and coins ... Bearb. von Dr. Hubert Jansen (xlviii p.)

Koran : manuscript, [1892-1896].

marginal notes/ examined by M. Zacharia 8/24/89."

‘Neutral, native-like or authentic’ : Investigating attitudes and beliefs of expanding circle speakers of English

The status of English as the language of international communication is by now well-established. However, in the past 16 years, research has tried to emphasize the fact that the English spoken in international contact situations and between people with other first languages than English has different needs than the English spoken locally amongst native speakers, resulting in the emergence of English as a lingua franca (ELF) as a scholarly field. However, the impact of findings in ELF has so far only led to a moderate shift in English language teaching. Especially in expanding circle countries, where ELF should have the biggest impact, change is only gradually becoming palpable. Accent and pronunciation, as one of the biggest factors on both identity and mutual intelligibility (Jenkins 2000; 2007) are at the root of discussion. The scope of this study is therefore to examine accent choices and the extent to which native speaker ideology informs the preferences of ten speakers of ELF and 27 German natives with experience in international communication. Both ethnographical and sociolinguistic methods, as well as auditory analysis have been applied and conducted. The auditory analysis of six variables in the recorded speech production of the ten speakers suggests that there is no significant preference of one norm-giving variety over the other. Rather, speakers tend to mix-and-match General American- and Standard Southern British English-like features in their pronunciation. When reporting their accent ideals, the idea of a ‘neutral’ English accent is mentioned by four participants. Neutral accents seem to have been understood as ‘unmarked accents’. Expressed beliefs on their own English pronunciation show a comparatively high level of reflection on and confidence in their own production. Results from a rating task and a survey given to 27 German participants reveal attitudes that are more negatively stacked. While Germans reported openness towards NNS (non-native speaker) accents and showed awareness of the priority of intelligibility over accent choice in both their own and others’ pronunciation, they still largely reported NS accent preference. The ratings of the production from ten ELF speakers confirmed this and showed that ‘neutral’ is equated with native-like. In the light of these findings, issues are discussed that ultimately relate to the influence of NS Englishes, identity and the development of English as an international language.